Hasil untuk "Industrial safety. Industrial accident prevention"

J. Takala, P. Hämäläinen, K. Saarela et al.

This article reviews the present indicators, trends, and recent solutions and strategies to tackle major global and country problems in safety and health at work. The article is based on the Yant Award Lecture of the American Industrial Hygiene Association (AIHA) at its 2013 Congress. We reviewed employment figures, mortality rates, occupational burden of disease and injuries, reported accidents, surveys on self-reported occupational illnesses and injuries, attributable fractions, national economic cost estimates of work-related injuries and ill health, and the most recent information on the problems from published papers, documents, and electronic data sources of international and regional organizations, in particular the International Labor Organization (ILO), World Health Organization (WHO), and European Union (EU), institutions, agencies, and public websites. We identified and analyzed successful solutions, programs, and strategies to reduce the work-related negative outcomes at various levels. Work-related illnesses that have a long latency period and are linked to ageing are clearly on the increase, while the number of occupational injuries has gone down in industrialized countries thanks to both better prevention and structural changes. We have estimated that globally there are 2.3 million deaths annually for reasons attributed to work. The biggest component is linked to work-related diseases, 2.0 million, and 0.3 million linked to occupational injuries. However, the division of these two factors varies depending on the level of development. In industrialized countries the share of deaths caused by occupational injuries and work-related communicable diseases is very low while non-communicable diseases are the overwhelming causes in those countries. Economic costs of work-related injury and illness vary between 1.8 and 6.0% of GDP in country estimates, the average being 4% according to the ILO. Singapore's economic costs were estimated to be equivalent to 3.2% of GDP based on a preliminary study. If economic losses would take into account involuntary early retirement then costs may be considerably higher, for example, in Finland up to 15% of GDP, while this estimate covers various disorders where work and working conditions may be just one factor of many or where work may aggravate the disease, injury, or disorders, such as traffic injuries, mental disorders, alcoholism, and genetically induced problems. Workplace health promotion, services, and safety and health management, however, may have a major preventive impact on those as well. Leadership and management at all levels, and engagement of workers are key issues in changing the workplace culture. Vision Zero is a useful concept and philosophy in gradually eliminating any harm at work. Legal and enforcement measures that themselves support companies and organizations need to be supplemented with economic justification and convincing arguments to reduce corner-cutting in risk management, and to avoid short- and long-term disabilities, premature retirement, and corporate closures due to mismanagement and poor and unsustainable work life. We consider that a new paradigm is needed where good work is not just considered a daily activity. We need to foster stable conditions and circumstances and sustainable work life where the objective is to maintain your health and work ability beyond the legal retirement age. We need safe and healthy work, for life.

Azar Ehrambaf Shooshtar, Parvaneh Samouei, Masumeh Messi Bidgoli

Background and objective Critical infrastructures, including water, electricity, and wastewater, are highly interdependent. Disruption in one of these systems can have a cascade effect on other systems and disrupt the entire system. In this research, to increase the resilience of these infrastructures against disasters, we aimed to model the interdependencies between them and prioritize critical nodes. Method Based on the data for the urban network of Sioux Falls in South Dakota reported in a previous study, and taking into account its critical infrastructures, we used the DEMATEL method and Root Assessment Method (RAM) to identify the critical points of these networks for strengthening them. The study network had 21 nodes and there were five main criteria of node capacity, supply node, transmission node, connection with other networks (such as communication) and repair cost, and three sub-criteria of electricity, water and wastewater systems. To prioritize the nodes, we first obtained the weights of each criterion using the DEMATEL method. Then, using the RAM, we prioritized critical nodes that needed to be strengthened interdependent critical infrastructures in the pre-disaster phase. Results Using the DEMATEL method, the results showed that the node capacity criterion was the most important criterion in decision-making. Also, in most cases, the electricity sub-criterion had the highest local weight. Using the RAM, the identified critical nodes were the nodes number 5, 6, 13, and 15. These nodes are usually transmission nodes or major facilities. Parameters such as capacity, repair time, and reinforcement cost play an important role in determining the importance of nodes. Conclusion The node capacity, as the most influential factor, plays a key role in managing and improving urban critical infrastructures. The identified critical points require more attention. Reinforcement of these nodes can significantly increase the resilience and performance of urban critical infrastructures. Also, special attention should be paid to the interdependencies between critical infrastructures and necessary measures should be taken to reduce the interdependency.

Wataru Katagiri, Masaaki Shimono, Shunsuke Eguchi et al.

Objectives: Hypertension and dyslipidemia are major risk factors of cardiovascular diseases. Nevertheless, many people do not consider these risk factors important, even if they are noted during their annual health checkups and left untreated for a long time. Here, we report a novel nudge method to encourage people who had these risk factors and examine the resultant changes in the willingness to undergo secondary health examinations. Methods: Employees of Novartis Pharma K.K. and its affiliated companies who had elevated blood pressure and/or lipid levels during annual health checkups were allocated to either the social nudge group (postcards were sent to their spouses) or the control group (postcards were sent to themselves) after confirming their agreement to receive postcards in order to encourage them to take secondary health examination. A web-based survey via email was conducted before and after sending the postcards to understand the willingness to undergo secondary health examinations. Results: Regarding the willingness to undergo the secondary health examinations, a significant difference was observed in the social nudge group (n=58) before (12.1%) and after (46.6%) the postcard was sent (p<0.0001), and no significant difference was observed in the control group (n=9, p=1.0000). The proportion of employees who underwent secondary health examinations did not increase significantly in either group. Conclusions: This study suggested that a social nudge via spouse has a possibility of increasing the willingness to undergo secondary health examinations at low cost. To increase the proportion of undergoing it, combinations with other nudges might be necessary.

Vade Shah, Yohan John, Ethan Freifeld et al.

Industrial refrigeration systems have substantial energy needs, but optimizing their operation remains challenging due to the tension between minimizing energy costs and meeting strict cooling requirements. Load shifting--strategic overcooling in anticipation of future demands--offers substantial efficiency gains. This work seeks to rigorously quantify these potential savings through the derivation of optimal load shifting policies. Our first contribution establishes a novel connection between industrial refrigeration and inventory control problems with convex ordering costs, where the convexity arises from the relationship between energy consumption and cooling capacity. Leveraging this formulation, we derive three main theoretical results: (1) an optimal algorithm for deterministic demand scenarios, along with proof that optimal trajectories are non-increasing (a valuable structural insight for practical control); (2) performance bounds that quantify the value of load shifting as a function of cost convexity, demand variability, and temporal patterns; (3) a computationally tractable load shifting heuristic with provable near-optimal performance under uncertainty. Numerical simulations validate our theoretical findings, and a case study using real industrial refrigeration data demonstrates an opportunity for improved load shifting.

Dimitris Kallis, Moysis Symeonides, Marios D. Dikaiakos

The widespread adoption of IoT has driven the development of cyber-physical systems (CPS) in industrial environments, leveraging Industrial IoTs (IIoTs) to automate manufacturing processes and enhance productivity. The transition to autonomous systems introduces significant operational costs, particularly in terms of energy consumption. Accurate modeling and prediction of IIoT energy requirements are critical, but traditional physics- and engineering-based approaches often fall short in addressing these challenges comprehensively. In this paper, we propose a novel methodology for benchmarking and analyzing IIoT devices and applications to uncover insights into their power demands, energy consumption, and performance. To demonstrate this methodology, we develop a comprehensive framework and apply it to study an industrial CPS comprising an educational robotic arm, a conveyor belt, a smart camera, and a compute node. By creating micro-benchmarks and an end-to-end application within this framework, we create an extensive performance and power consumption dataset, which we use to train and analyze ML models for predicting energy usage from features of the application and the CPS system. The proposed methodology and framework provide valuable insights into the energy dynamics of industrial CPS, offering practical implications for researchers and practitioners aiming to enhance the efficiency and sustainability of IIoT-driven automation.

Francesc Sabater, Ouns El Harzli, Geert-Jan Besjes et al.

Optimization via decoded quantum interferometry (DQI) has recently gained a great deal of attention as a promising avenue for solving optimization problems using quantum computers. In this paper, we apply DQI to an industrial optimization problem in the automotive industry: the vehicle option-package pricing problem. Our main contributions are 1) formulating the industrial problem as an integer linear program (ILP), 2) converting the ILP into instances of max-XORSAT, and 3) developing a detailed quantum circuit implementation for belief propagation, a heuristic algorithm for decoding LDPC codes. Thus, we provide a full implementation of the DQI algorithm using Belief Propagation, which can be applied to any industrially relevant ILP by first transforming it into a max-XORSAT instance. We also evaluate the effectiveness of our implementation by benchmarking it against both Gurobi and a random sampling baseline.

Georg K. J. Fischer, Max Bergau, D. Adriana Gómez-Rosal et al.

Automated and autonomous industrial inspection is a longstanding research field, driven by the necessity to enhance safety and efficiency within industrial settings. In addressing this need, we introduce an autonomously navigating robotic system designed for comprehensive plant inspection. This innovative system comprises a robotic platform equipped with a diverse array of sensors integrated to facilitate the detection of various process and infrastructure parameters. These sensors encompass optical (LiDAR, Stereo, UV/IR/RGB cameras), olfactory (electronic nose), and acoustic (microphone array) capabilities, enabling the identification of factors such as methane leaks, flow rates, and infrastructural anomalies. The proposed system underwent individual evaluation at a wastewater treatment site within a chemical plant, providing a practical and challenging environment for testing. The evaluation process encompassed key aspects such as object detection, 3D localization, and path planning. Furthermore, specific evaluations were conducted for optical methane leak detection and localization, as well as acoustic assessments focusing on pump equipment and gas leak localization.

Anju Rani, Daniel Ortiz-Arroyo, Petar Durdevic

In recent years, 3D point clouds (PCs) have gained significant attention due to their diverse applications across various fields, such as computer vision (CV), condition monitoring (CM), virtual reality, robotics, autonomous driving, etc. Deep learning (DL) has proven effective in leveraging 3D PCs to address various challenges encountered in 2D vision. However, applying deep neural networks (DNNs) to process 3D PCs presents unique challenges. This paper provides an in-depth review of recent advancements in DL-based industrial CM using 3D PCs, with a specific focus on defect shape classification and segmentation within industrial applications. Recognizing the crucial role of these aspects in industrial maintenance, the paper offers insightful observations on the strengths and limitations of the reviewed DL-based PC processing methods. This knowledge synthesis aims to contribute to understanding and enhancing CM processes, particularly within the framework of remaining useful life (RUL), in industrial systems.

Amit Kumar, Jaison Jose, Archit Jain et al.

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal Robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months.

Yuiki Iwayama, Yuki Shimba, Chandra Sekhar Viswanathan et al.

Objectives: Specific health guidance (SHG) has served as a preventive intervention for metabolic syndrome in Japan since 2008. For SHG, health professionals guide diet and physical activity to achieve body weight (BW) and waist circumference (WC) reductions. Since 2013, SHG intervention using information and communication technology (ICT-based SHG) has also been available. Therefore, in this study, we examined the effects of ICT-based SHG, and identified factors associated with BW and WC reductions in response to this intervention. Methods: Our intervention was performed using a smartphone application with videophone guidance and message exchanges provided by health professionals. We analysed 1,994 participants. Primary outcomes included changes in BW and WC after versus before the intervention. We used multiple linear regression analyses to identify factors associated with reductions in BW and WC due to the intervention. Results: The mean ages were 49.3 (standard deviation [SD], 5.8) years for males and 50.5 (SD, 5.8) years for females. The mean BW change was −1.37 kg for both sexes. The mean WC changes were −1.05 for males and −2.05 cm for females. For males, baseline body mass index, pre-intervention action history, and the numbers of videophone communications and messages were significantly associated with larger changes in BW and WC. For females, no factors were significant for BW reduction, while baseline WC and pre-intervention action history were associated with WC reduction. Conclusions: ICT-based SHG reduces BW and WC. Videophone communication and messaging are associated with reductions in BW and WC in males. These results may help to improve the efficacy of ICT-based SHG.

J. Larouzée, J. L. Coze

Abstract This article provides a historical and critical account of James Reason’s contribution to safety research with a focus on the Swiss cheese model (SCM), its developments and its critics. This article shows that the SCM is a product of specific historical circumstances, has been developed over a ten years period following several steps, and has benefited of the direct influence of John Wreathall. Reason took part in intense intellectual debates and publications in the 1980s during which many ideas circulated among researchers, featuring authors as influent as Donald Norman, Jens Rasmussen, Charles Perrow or Barry Turner. The 1980s and 1990s were highly productive from a safety research point of view (e.g. human error, incubation models, high reliability organisation, safety culture) and Reason has considerably influenced it with a rich production of models, based on both research and industrial projects. Historical perspectives offer interesting insights because they can question research, the conditions of its production, its relevance and, sometimes, its success, as for the SCM. But, because of this success, critics have vividly argued about some of the SCM limitations, including its simplistic vision of accidents and its degree of generality. Against these positions, the article develops a ‘critique of the criticism’, and the article concludes that the SCM remains a relevant model because of its systemic foundations and its sustained use in high-risk industries; despite of course, the need to keep imagining alternatives based on the mix of collective empirical, practical and graphical research which was in the SCM background.

Soobin Kim, Minjeong Kim, Hyein Kim et al.

Chemical accidents have threatened drinking water safety and aquatic systems when hazardous chemicals flow into inland waterbodies through pipelines in industrial complexes. In this study, a forecasting system was developed for the prevention of drinking water resource pollution by considering chemical transport/fate through both pipelines and river channels. To this end, we coupled a pipe network model (Storm Water Management Model) with a calibrated hydrodynamic model (Environmental Fluid Dynamics Code). In addition, we investigated whether chemical transport through pipelines would make a difference in chemical concentration predictions. For both pipelines and river channels, the results showed lower peak concentrations than those without pipelines, whereas the time of peak concentration did not change significantly. When chemicals were transported with both pipelines and river channels, the peak concentrations were 25.81% and 41.91% lower than those of chemicals carried directly into the Han and Geum Rivers without the pipeline transport. Further, our system is automated from scenario generation to analysis and usage is straightforward, with a simple input of accident information. The results of this study can be utilized to establish a safe water supply system and preliminary countermeasures against accidental water pollution in the future.

Hyun Jeong Seo, Ah Jeong Hong

In order to derive safety engagement factors in the workplace and analyze the characteristics of the factors, we collected literature data to be analyzed by a systematic literature review and text mining analysis. We used safety, industrial, occupational, corporate, commitment, engagement, interaction, and participation as key search terms for literature selection and used 143 literature datasets for analysis. We divided the factors of workplace safety engagement into the organizational level and the individual level. In studies after 2005, texts at the individual psychological level appeared in large numbers. Although individual factors have been studied as subfactors at the organizational level, we confirmed that the two types of factors must interact for safety engagement in the workplace. We classified safety engagement factors into cognitive, emotional, behavioral, and relational factors. In particular, relational factors were mainly composed of factors that negatively affected engagement. In the follow-up study, we identified the maturity level among safety engagement factors as divided into four dimensions needed to create a safe workplace environment and to suggest a direction for employees to engage themselves in safety.

Maleeha MIRHOSSEINI, Mahmoud MOINUDDIN, Forough HIRANI et al.

Introduction: Ethics is a pervasive subject which covers all aspects of human life. The rapid growth of human society and the complexity of social relations require the emergence of various professions. Survival of these professions depends on the type and quality of services they provide and the trust and credibility that they gain as a result of providing these services. To increase the impact of professional ethics, it is necessary to have patterns consistent with culture and society, and by recognizing them, the dimensions of safe behavior by accountants can be explored. Research Method: This was an applied study in terms of purpose, and based on the research method, it was both quantitative and qualitative. The statistical population consisted of published domestic papers related to accounting professional ethics. In this study, effective criteria based on previous research were identified and selected in the form of 5 main indicators. Then, a researcher-made questionnaire was designed and implemented to determine the fuzzy cognition mapping pattern. Findings: Fuzzy cognition mapping among 5 main components showed that there is a cause and effect relationship between all components. However, this cause and effect relationship is positive in some cases and negative in others. Results indicated that an individual component has a negative relationship with an organizational component and a positive relationship with other components. Social component has a positive relationship only with the individual component and a negative relationship with other components. In other words, social component is inversely related to organizational, professionalism and environmental indicators, and the highest intensity of the reverse flow is related to the environmental component. Conclusion: By understanding professional ethics of accountants and identifying its basic components and determining the relationship between these components in different dimensions and specifying the importance of each of them, a specific framework or format can be designed and implemented for observing or not observing professional ethics by accountants and the desire to behave based on the code of professional behavior .This is to reduce unsafe behaviors, and as a result, reduce the rate of accidents in the country's industries.

Birgit Vogel-Heuser, Eva-Maria Neumann, Juliane Fischer

automated Production Systems (aPS) are highly complex, mechatronic systems that usually have to operate reliably for many decades. Standardization and reuse of control software modules is a core prerequisite to achieve the required system quality in increasingly shorter development cycles. However, industrial case studies in the field of aPS show that many aPS companies still struggle with strategically reusing software. This paper proposes a metric-based approach to objectively measure the maturity of industrial IEC 61131-based control software in aPS (MICOSE4aPS) to identify potential weaknesses and quality issues hampering systematic reuse. Module developers in the machine and plant manufacturing industry can directly benefit as the metric calculation is integrated into the software engineering workflow. An in-depth industrial evaluation in a top-ranked machine manufacturing company in food packaging and an expert evaluation with different companies confirmed the benefit to efficiently manage the quality of control software.

Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou et al.

Industrial analytics that includes among others equipment diagnosis and anomaly detection heavily relies on integration of heterogeneous production data. Knowledge Graphs (KGs) as the data format and ontologies as the unified data schemata are a prominent solution that offers high quality data integration and a convenient and standardised way to exchange data and to layer analytical applications over it. However, poor design of ontologies of high degree of mismatch between them and industrial data naturally lead to KGs of low quality that impede the adoption and scalability of industrial analytics. Indeed, such KGs substantially increase the training time of writing queries for users, consume high volume of storage for redundant information, and are hard to maintain and update. To address this problem we propose an ontology reshaping approach to transform ontologies into KG schemata that better reflect the underlying data and thus help to construct better KGs. In this poster we present a preliminary discussion of our on-going research, evaluate our approach with a rich set of SPARQL queries on real-world industry data at Bosch and discuss our findings.

Rohit Gupta, Nico Jansen, Nikolaus Regnat et al.

Domain-specific modelling languages (DSMLs) help practitioners solve modelling challenges specific to various domains. As domains grow more complex and heterogeneous in nature, industrial practitioners often face challenges in the usability of graphical DSMLs. There is still a lack of guidelines that industrial language engineers should consider for improving the user experience (UX) of these practitioners. The overall topic of UX is vast and subjective, and general guidelines and definitions of UX are often overly generic or tied to specific technological spaces. To solve this challenge, we leverage existing design principles and standards of human-centred design and UX in general and propose definitions and guidelines for UX and user experience design (UXD) aspects in graphical DSMLs. In this paper, we categorize the key UXD aspects, primarily based on our experience in developing industrial DSMLs, that language engineers should consider during graphical DSML development. Ultimately, these UXD guidelines help to improve the general usability of industrial DSMLs and support language engineers in developing better DSMLs that are independent of graphical modelling tools and more widely accepted by their users.

Monalisa Ma'rifat, Atiya Thifal Rofifa, Tri Martiana

Introduction: The plate manufacturing production unit is one of the work units in PT. INKA (Persero), which involves the interaction between humans and machines in its activities, heavy equipment, and materials, all of which can cause possible hazard impacts that can impact the safety and health of workers. The purpose of this study is to conduct risk assessment on occupational safety and health aspects by identifying risks, assessing risks, identifying control efforts and assessing residual risk as a form of efforts to prevent occupational accidents and occupational diseases, using existing resources effectively and efficiently. Method: This research is a type of qualitative research, through interviews and observations, with cross-sectional studies and descriptive analysis. The interviewees for this study were K3LH management managers, steel managers, and machine operators in the plate production unit (PPL). The tools in this study werean interview guide, Job Safety Analysis (JSA) and Hazard Identification Risk Assessment Determining Control (HIRADC) using the AS / NZS 4360: 2004 Risk Management Worksheet Standard Risk Matrix. Results: From the research, it was found that there are 94 hazards for 11 different machines. Regarding the risk levels, there are 9 extreme risk levels, 46 high risk levels, 33 medium risk levels and 6 low risk levels. Conclusion: There are still 61 risks with medium risk level and 6 remaining risks with high risk level that still need control. Control efforts have been implemented by PT. INKA (Persero) in accordance with the hierarchy of control, such as the use of PPE and the provision of work SOPs.   Keywords: hazard identification, risk management, risk assessment, risk control, residual risk

А.Б. Елькин, И.А. Евсеева

Yurii Kravchenko, Yevhenii Makhno , Maksym Tyshchenko et al.

У статті висвітлено дослідження в галузі штучного інтелекту в якості науки, яка займається створенням інтелектуалізованих автоматичних систем. Досліджено аспекти технології створення систем штучного інтелекту, а також розкрито ряд підходів до їх створення. Вказано місце інтелектуалізації адміністрування систем дистанційного навчання. У статті йдеться про перспективи штучного інтелекту, який постійно трансформується, змінюється залежно від нових тенденцій та викликів сьогодення, а також про вбачання шляхів його подальшого розвитку, підходи до вивчення та функціонування. Наразі перспективними напрямками в умовах обмежень освітнього процесу є інтелектуалізація елементів адміністрування та автоматизація певних навчальних компонентів у системах дистанційного навчання. Інтелектуалізація адміністрування у освітньому процесі дасть можливість автоматизувати ряд рутинних, типових завдань, які потребують людських ресурсів і забирають багато часу. Одним з них є планування часу на виконання навчального завдання в системі дистанційного навчання. У статті подано модель інтелектуалізації цього процесу. Це лише перші кроки на шляху до створення потужного штучного інтелекту щодо сфери освіти у військовій галузі.